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DBMS > Amazon DocumentDB vs. FoundationDB vs. LevelDB vs. Solr

System Properties Comparison Amazon DocumentDB vs. FoundationDB vs. LevelDB vs. Solr

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonFoundationDB  Xexclude from comparisonLevelDB  Xexclude from comparisonSolr  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceOrdered key-value store. Core features are complimented by layers.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument storeDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Key-value storeSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score1.06
Rank#185  Overall
#31  Document stores
#28  Key-value stores
#85  Relational DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Score41.02
Rank#24  Overall
#3  Search engines
Websiteaws.amazon.com/­documentdbgithub.com/­apple/­foundationdbgithub.com/­google/­leveldbsolr.apache.org
Technical documentationaws.amazon.com/­documentdb/­resourcesapple.github.io/­foundationdbgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdsolr.apache.org/­resources.html
DeveloperFoundationDBGoogleApache Software Foundation
Initial release2019201320112006
Current release6.2.28, November 20201.23, February 20219.6.1, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoBSDOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++Java
Server operating systemshostedLinux
OS X
Windows
Illumos
Linux
OS X
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeschema-free infosome layers support schemasschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesno infosome layers support typingnoyes infosupports customizable data types and automatic typing
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonoyes
Secondary indexesyesnonoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnosupported in specific SQL layer onlynoSolr Parallel SQL Interface
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Java API
RESTful HTTP/JSON API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoin SQL-layer onlynoJava plugins
Triggersnononoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyLinearizable consistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblein SQL-layer onlynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlAccess rights for users and rolesnonoyes

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More resources
Amazon DocumentDBFoundationDBLevelDBSolr
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